Pandas Profiling Report

Dataset statistics

Number of variables	21
Number of observations	41188
Missing cells	12718
Missing cells (%)	1.5%
Duplicate rows	10
Duplicate rows (%)	< 0.1%
Total size in memory	29.9 MiB
Average record size in memory	760.5 B

Variable types

Numeric	10
Categorical	7
Boolean	4

Warnings

Dataset has 10 (< 0.1%) duplicate rows	Duplicates
`previous_contacts` is highly correlated with `no_of_employees`	High correlation
`emp_var_rate` is highly correlated with `cons_price_idx` and 2 other fields	High correlation
`cons_price_idx` is highly correlated with `emp_var_rate` and 2 other fields	High correlation
`euribor3m` is highly correlated with `emp_var_rate` and 2 other fields	High correlation
`no_of_employees` is highly correlated with `previous_contacts` and 3 other fields	High correlation
`passed_days` is highly correlated with `previous_contacts`	High correlation
`previous_contacts` is highly correlated with `passed_days`	High correlation
`emp_var_rate` is highly correlated with `cons_price_idx` and 2 other fields	High correlation
`cons_price_idx` is highly correlated with `emp_var_rate`	High correlation
`euribor3m` is highly correlated with `emp_var_rate` and 1 other fields	High correlation
`no_of_employees` is highly correlated with `emp_var_rate` and 1 other fields	High correlation
`age` is highly correlated with `passed_days` and 1 other fields	High correlation
`duration` is highly correlated with `passed_days` and 1 other fields	High correlation
`no_of_contacts` is highly correlated with `passed_days` and 1 other fields	High correlation
`passed_days` is highly correlated with `age` and 3 other fields	High correlation
`previous_contacts` is highly correlated with `age` and 3 other fields	High correlation
`emp_var_rate` is highly correlated with `euribor3m`	High correlation
`euribor3m` is highly correlated with `emp_var_rate`	High correlation
`emp_var_rate` is highly correlated with `last_Cmonth` and 6 other fields	High correlation
`y` is highly correlated with `cons_conf_idx` and 2 other fields	High correlation
`last_Cmonth` is highly correlated with `emp_var_rate` and 5 other fields	High correlation
`cons_conf_idx` is highly correlated with `emp_var_rate` and 7 other fields	High correlation
`no_of_employees` is highly correlated with `emp_var_rate` and 7 other fields	High correlation
`contact_type` is highly correlated with `emp_var_rate` and 5 other fields	High correlation
`passed_days` is highly correlated with `previous_outcome`	High correlation
`job_type` is highly correlated with `education_level` and 1 other fields	High correlation
`cons_price_idx` is highly correlated with `emp_var_rate` and 6 other fields	High correlation
`euribor3m` is highly correlated with `emp_var_rate` and 8 other fields	High correlation
`education_level` is highly correlated with `job_type`	High correlation
`previous_contacts` is highly correlated with `euribor3m` and 1 other fields	High correlation
`age` is highly correlated with `job_type`	High correlation
`previous_outcome` is highly correlated with `emp_var_rate` and 6 other fields	High correlation
`last_Cmonth` is highly correlated with `contact_type`	High correlation
`contact_type` is highly correlated with `last_Cmonth`	High correlation
`education_level` has 1731 (4.2%) missing values	Missing
`default_credit` has 8597 (20.9%) missing values	Missing
`housing_loan` has 990 (2.4%) missing values	Missing
`personal_loan` has 990 (2.4%) missing values	Missing
`passed_days` has 39688 (96.4%) zeros	Zeros
`previous_contacts` has 35563 (86.3%) zeros	Zeros

Reproduction

Analysis started	2021-08-14 11:29:12.792654
Analysis finished	2021-08-14 11:31:09.087650
Duration	1 minute and 56.29 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	78
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	40.02406041

Minimum	17
Maximum	98
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	17
5-th percentile	26
Q1	32
median	38
Q3	47
95-th percentile	58
Maximum	98
Range	81
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	10.42124998
Coefficient of variation (CV)	0.2603746315
Kurtosis	0.7913115312
Mean	40.02406041
Median Absolute Deviation (MAD)	7
Skewness	0.7846968158
Sum	1648511
Variance	108.6024512
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31	1947	4.7%
32	1846	4.5%
33	1833	4.5%
36	1780	4.3%
35	1759	4.3%
34	1745	4.2%
30	1714	4.2%
37	1475	3.6%
29	1453	3.5%
39	1432	3.5%
Other values (68)	24204	58.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
17	5	< 0.1%
18	28	0.1%
19	42	0.1%
20	65	0.2%
21	102	0.2%
22	137	0.3%
23	226	0.5%
24	463	1.1%
25	598	1.5%
26	698	1.7%

Value	Count	Frequency (%)
98	2	< 0.1%
95	1	< 0.1%
94	1	< 0.1%
92	4	< 0.1%
91	2	< 0.1%
89	2	< 0.1%
88	22	0.1%
87	1	< 0.1%
86	8	< 0.1%
85	15	< 0.1%

job_type
Categorical

HIGH CORRELATION

Distinct	11
Distinct (%)	< 0.1%
Missing	330
Missing (%)	0.8%
Memory size	2.6 MiB

admin.	10422
blue-collar	9254
technician	6743
services	3969
management	2924
Other values (6)	7546

Length

Max length	13
Median length	10
Mean length	8.971021587
Min length	6

Characters and Unicode

Total characters	366538
Distinct characters	22
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	housemaid
2nd row	services
3rd row	services
4th row	admin.
5th row	services

Common Values

Value	Count	Frequency (%)
admin.	10422	25.3%
blue-collar	9254	22.5%
technician	6743	16.4%
services	3969	9.6%
management	2924	7.1%
retired	1720	4.2%
entrepreneur	1456	3.5%
self-employed	1421	3.5%
housemaid	1060	2.6%
unemployed	1014	2.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
admin	10422	25.5%
blue-collar	9254	22.6%
technician	6743	16.5%
services	3969	9.7%
management	2924	7.2%
retired	1720	4.2%
entrepreneur	1456	3.6%
self-employed	1421	3.5%
housemaid	1060	2.6%
unemployed	1014	2.5%

Most occurring characters

Value	Count	Frequency (%)
e	47273	12.9%
n	34557	9.4%
a	33327	9.1%
l	31618	8.6%
i	30657	8.4%
c	26709	7.3%
r	21031	5.7%
m	19765	5.4%
d	16512	4.5%
t	14593	4.0%
Other values (12)	90496	24.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	345441	94.2%
Dash Punctuation	10675	2.9%
Other Punctuation	10422	2.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	47273	13.7%
n	34557	10.0%
a	33327	9.6%
l	31618	9.2%
i	30657	8.9%
c	26709	7.7%
r	21031	6.1%
m	19765	5.7%
d	16512	4.8%
t	14593	4.2%
Other values (10)	69399	20.1%

Other Punctuation

Value	Count	Frequency (%)
.	10422	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	10675	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	345441	94.2%
Common	21097	5.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	47273	13.7%
n	34557	10.0%
a	33327	9.6%
l	31618	9.2%
i	30657	8.9%
c	26709	7.7%
r	21031	6.1%
m	19765	5.7%
d	16512	4.8%
t	14593	4.2%
Other values (10)	69399	20.1%

Common

Value	Count	Frequency (%)
-	10675	50.6%
.	10422	49.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	366538	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	47273	12.9%
n	34557	9.4%
a	33327	9.1%
l	31618	8.6%
i	30657	8.4%
c	26709	7.3%
r	21031	5.7%
m	19765	5.4%
d	16512	4.5%
t	14593	4.0%
Other values (12)	90496	24.7%

marital_status
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	80
Missing (%)	0.2%
Memory size	2.5 MiB

married	24928
single	11568
divorced	4612

Length

Max length	8
Median length	7
Mean length	6.830787195
Min length	6

Characters and Unicode

Total characters	280800
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	married
2nd row	married
3rd row	married
4th row	married
5th row	married

Common Values

Value	Count	Frequency (%)
married	24928	60.5%
single	11568	28.1%
divorced	4612	11.2%
(Missing)	80	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
married	24928	60.6%
single	11568	28.1%
divorced	4612	11.2%

Most occurring characters

Value	Count	Frequency (%)
r	54468	19.4%
i	41108	14.6%
e	41108	14.6%
d	34152	12.2%
m	24928	8.9%
a	24928	8.9%
s	11568	4.1%
n	11568	4.1%
g	11568	4.1%
l	11568	4.1%
Other values (3)	13836	4.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	280800	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	54468	19.4%
i	41108	14.6%
e	41108	14.6%
d	34152	12.2%
m	24928	8.9%
a	24928	8.9%
s	11568	4.1%
n	11568	4.1%
g	11568	4.1%
l	11568	4.1%
Other values (3)	13836	4.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	280800	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	54468	19.4%
i	41108	14.6%
e	41108	14.6%
d	34152	12.2%
m	24928	8.9%
a	24928	8.9%
s	11568	4.1%
n	11568	4.1%
g	11568	4.1%
l	11568	4.1%
Other values (3)	13836	4.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	280800	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	54468	19.4%
i	41108	14.6%
e	41108	14.6%
d	34152	12.2%
m	24928	8.9%
a	24928	8.9%
s	11568	4.1%
n	11568	4.1%
g	11568	4.1%
l	11568	4.1%
Other values (3)	13836	4.9%

education_level
Categorical

HIGH CORRELATION
MISSING

Distinct	7
Distinct (%)	< 0.1%
Missing	1731
Missing (%)	4.2%
Memory size	2.7 MiB

university.degree	12168
high.school	9515
basic.9y	6045
professional.course	5243
basic.4y	4176
Other values (2)	2310

Length

Max length	19
Median length	11
Mean length	12.9615024
Min length	8

Characters and Unicode

Total characters	511422
Distinct characters	23
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	basic.4y
2nd row	high.school
3rd row	high.school
4th row	basic.6y
5th row	high.school

Common Values

Value	Count	Frequency (%)
university.degree	12168	29.5%
high.school	9515	23.1%
basic.9y	6045	14.7%
professional.course	5243	12.7%
basic.4y	4176	10.1%
basic.6y	2292	5.6%
illiterate	18	< 0.1%
(Missing)	1731	4.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
university.degree	12168	30.8%
high.school	9515	24.1%
basic.9y	6045	15.3%
professional.course	5243	13.3%
basic.4y	4176	10.6%
basic.6y	2292	5.8%
illiterate	18	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
e	59194	11.6%
i	51643	10.1%
s	49925	9.8%
.	39439	7.7%
r	34840	6.8%
o	34759	6.8%
h	28545	5.6%
c	27271	5.3%
y	24681	4.8%
g	21683	4.2%
Other values (13)	139442	27.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	459470	89.8%
Other Punctuation	39439	7.7%
Decimal Number	12513	2.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	59194	12.9%
i	51643	11.2%
s	49925	10.9%
r	34840	7.6%
o	34759	7.6%
h	28545	6.2%
c	27271	5.9%
y	24681	5.4%
g	21683	4.7%
a	17774	3.9%
Other values (9)	109155	23.8%

Decimal Number

Value	Count	Frequency (%)
9	6045	48.3%
4	4176	33.4%
6	2292	18.3%

Other Punctuation

Value	Count	Frequency (%)
.	39439	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	459470	89.8%
Common	51952	10.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	59194	12.9%
i	51643	11.2%
s	49925	10.9%
r	34840	7.6%
o	34759	7.6%
h	28545	6.2%
c	27271	5.9%
y	24681	5.4%
g	21683	4.7%
a	17774	3.9%
Other values (9)	109155	23.8%

Common

Value	Count	Frequency (%)
.	39439	75.9%
9	6045	11.6%
4	4176	8.0%
6	2292	4.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	511422	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	59194	11.6%
i	51643	10.1%
s	49925	9.8%
.	39439	7.7%
r	34840	6.8%
o	34759	6.8%
h	28545	5.6%
c	27271	5.3%
y	24681	4.8%
g	21683	4.2%
Other values (13)	139442	27.3%

default_credit
Boolean

MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	8597
Missing (%)	20.9%
Memory size	80.6 KiB

False	32588
True	3
(Missing)	8597

Common Values
Chart

Value	Count	Frequency (%)
False	32588	79.1%
True	3	< 0.1%
(Missing)	8597	20.9%

housing_loan
Boolean

MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	990
Missing (%)	2.4%
Memory size	80.6 KiB

True	21576
False	18622
(Missing)	990

Common Values
Chart

Value	Count	Frequency (%)
True	21576	52.4%
False	18622	45.2%
(Missing)	990	2.4%

personal_loan
Boolean

MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	990
Missing (%)	2.4%
Memory size	80.6 KiB

False	33950
True	6248
(Missing)	990

Common Values
Chart

Value	Count	Frequency (%)
False	33950	82.4%
True	6248	15.2%
(Missing)	990	2.4%

contact_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.6 MiB

cellular	26144
telephone	15044

Length

Max length	9
Median length	8
Mean length	8.365252015
Min length	8

Characters and Unicode

Total characters	344548
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	telephone
2nd row	telephone
3rd row	telephone
4th row	telephone
5th row	telephone

Common Values

Value	Count	Frequency (%)
cellular	26144	63.5%
telephone	15044	36.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
cellular	26144	63.5%
telephone	15044	36.5%

Most occurring characters

Value	Count	Frequency (%)
l	93476	27.1%
e	71276	20.7%
c	26144	7.6%
u	26144	7.6%
a	26144	7.6%
r	26144	7.6%
t	15044	4.4%
p	15044	4.4%
h	15044	4.4%
o	15044	4.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	344548	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	93476	27.1%
e	71276	20.7%
c	26144	7.6%
u	26144	7.6%
a	26144	7.6%
r	26144	7.6%
t	15044	4.4%
p	15044	4.4%
h	15044	4.4%
o	15044	4.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	344548	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	93476	27.1%
e	71276	20.7%
c	26144	7.6%
u	26144	7.6%
a	26144	7.6%
r	26144	7.6%
t	15044	4.4%
p	15044	4.4%
h	15044	4.4%
o	15044	4.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	344548	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	93476	27.1%
e	71276	20.7%
c	26144	7.6%
u	26144	7.6%
a	26144	7.6%
r	26144	7.6%
t	15044	4.4%
p	15044	4.4%
h	15044	4.4%
o	15044	4.4%

last_Cmonth
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.4 MiB

may	13769
jul	7174
aug	6178
jun	5318
nov	4101
Other values (5)	4648

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	123564
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	may
2nd row	may
3rd row	may
4th row	may
5th row	may

Common Values

Value	Count	Frequency (%)
may	13769	33.4%
jul	7174	17.4%
aug	6178	15.0%
jun	5318	12.9%
nov	4101	10.0%
apr	2632	6.4%
oct	718	1.7%
sep	570	1.4%
mar	546	1.3%
dec	182	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
may	13769	33.4%
jul	7174	17.4%
aug	6178	15.0%
jun	5318	12.9%
nov	4101	10.0%
apr	2632	6.4%
oct	718	1.7%
sep	570	1.4%
mar	546	1.3%
dec	182	0.4%

Most occurring characters

Value	Count	Frequency (%)
a	23125	18.7%
u	18670	15.1%
m	14315	11.6%
y	13769	11.1%
j	12492	10.1%
n	9419	7.6%
l	7174	5.8%
g	6178	5.0%
o	4819	3.9%
v	4101	3.3%
Other values (7)	9502	7.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	123564	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	23125	18.7%
u	18670	15.1%
m	14315	11.6%
y	13769	11.1%
j	12492	10.1%
n	9419	7.6%
l	7174	5.8%
g	6178	5.0%
o	4819	3.9%
v	4101	3.3%
Other values (7)	9502	7.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	123564	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	23125	18.7%
u	18670	15.1%
m	14315	11.6%
y	13769	11.1%
j	12492	10.1%
n	9419	7.6%
l	7174	5.8%
g	6178	5.0%
o	4819	3.9%
v	4101	3.3%
Other values (7)	9502	7.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	123564	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	23125	18.7%
u	18670	15.1%
m	14315	11.6%
y	13769	11.1%
j	12492	10.1%
n	9419	7.6%
l	7174	5.8%
g	6178	5.0%
o	4819	3.9%
v	4101	3.3%
Other values (7)	9502	7.7%

last_Cday
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.4 MiB

thu	8623
mon	8514
wed	8134
tue	8090
fri	7827

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	123564
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	mon
2nd row	mon
3rd row	mon
4th row	mon
5th row	mon

Common Values

Value	Count	Frequency (%)
thu	8623	20.9%
mon	8514	20.7%
wed	8134	19.7%
tue	8090	19.6%
fri	7827	19.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
thu	8623	20.9%
mon	8514	20.7%
wed	8134	19.7%
tue	8090	19.6%
fri	7827	19.0%

Most occurring characters

Value	Count	Frequency (%)
t	16713	13.5%
u	16713	13.5%
e	16224	13.1%
h	8623	7.0%
m	8514	6.9%
o	8514	6.9%
n	8514	6.9%
w	8134	6.6%
d	8134	6.6%
f	7827	6.3%
Other values (2)	15654	12.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	123564	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	16713	13.5%
u	16713	13.5%
e	16224	13.1%
h	8623	7.0%
m	8514	6.9%
o	8514	6.9%
n	8514	6.9%
w	8134	6.6%
d	8134	6.6%
f	7827	6.3%
Other values (2)	15654	12.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	123564	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	16713	13.5%
u	16713	13.5%
e	16224	13.1%
h	8623	7.0%
m	8514	6.9%
o	8514	6.9%
n	8514	6.9%
w	8134	6.6%
d	8134	6.6%
f	7827	6.3%
Other values (2)	15654	12.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	123564	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	16713	13.5%
u	16713	13.5%
e	16224	13.1%
h	8623	7.0%
m	8514	6.9%
o	8514	6.9%
n	8514	6.9%
w	8134	6.6%
d	8134	6.6%
f	7827	6.3%
Other values (2)	15654	12.7%

duration
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	1544
Distinct (%)	3.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	258.2850102

Minimum	0
Maximum	4918
Zeros	4
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	0
5-th percentile	36
Q1	102
median	180
Q3	319
95-th percentile	752.65
Maximum	4918
Range	4918
Interquartile range (IQR)	217

Descriptive statistics

Standard deviation	259.2792488
Coefficient of variation (CV)	1.003849386
Kurtosis	20.24793801
Mean	258.2850102
Median Absolute Deviation (MAD)	94
Skewness	3.263141255
Sum	10638243
Variance	67225.72888
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
90	170	0.4%
85	170	0.4%
136	168	0.4%
73	167	0.4%
124	164	0.4%
87	162	0.4%
72	161	0.4%
104	161	0.4%
111	160	0.4%
106	159	0.4%
Other values (1534)	39546	96.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4	< 0.1%
1	3	< 0.1%
2	1	< 0.1%
3	3	< 0.1%
4	12	< 0.1%
5	30	0.1%
6	37	0.1%
7	54	0.1%
8	69	0.2%
9	77	0.2%

Value	Count	Frequency (%)
4918	1	< 0.1%
4199	1	< 0.1%
3785	1	< 0.1%
3643	1	< 0.1%
3631	1	< 0.1%
3509	1	< 0.1%
3422	1	< 0.1%
3366	1	< 0.1%
3322	1	< 0.1%
3284	1	< 0.1%

no_of_contacts
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	42
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.567592503

Minimum	1
Maximum	56
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	7
Maximum	56
Range	55
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.770013543
Coefficient of variation (CV)	1.078836903
Kurtosis	36.97979514
Mean	2.567592503
Median Absolute Deviation (MAD)	1
Skewness	4.762506697
Sum	105754
Variance	7.672975028
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=42)

Value	Count	Frequency (%)
1	17642	42.8%
2	10570	25.7%
3	5341	13.0%
4	2651	6.4%
5	1599	3.9%
6	979	2.4%
7	629	1.5%
8	400	1.0%
9	283	0.7%
10	225	0.5%
Other values (32)	869	2.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	17642	42.8%
2	10570	25.7%
3	5341	13.0%
4	2651	6.4%
5	1599	3.9%
6	979	2.4%
7	629	1.5%
8	400	1.0%
9	283	0.7%
10	225	0.5%

Value	Count	Frequency (%)
56	1	< 0.1%
43	2	< 0.1%
42	2	< 0.1%
41	1	< 0.1%
40	2	< 0.1%
39	1	< 0.1%
37	1	< 0.1%
35	5	< 0.1%
34	3	< 0.1%
33	4	< 0.1%

passed_days
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	26
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.2212294843

Minimum	0
Maximum	27
Zeros	39688
Zeros (%)	96.4%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	27
Range	27
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.348874125
Coefficient of variation (CV)	6.097171585
Kurtosis	76.40203714
Mean	0.2212294843
Median Absolute Deviation (MAD)	0
Skewness	7.939537186
Sum	9112
Variance	1.819461406
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
0	39688	96.4%
3	439	1.1%
6	412	1.0%
4	118	0.3%
9	64	0.2%
2	61	0.1%
7	60	0.1%
12	58	0.1%
10	52	0.1%
5	46	0.1%
Other values (16)	190	0.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	39688	96.4%
1	26	0.1%
2	61	0.1%
3	439	1.1%
4	118	0.3%
5	46	0.1%
6	412	1.0%
7	60	0.1%
8	18	< 0.1%
9	64	0.2%

Value	Count	Frequency (%)
27	1	< 0.1%
26	1	< 0.1%
25	1	< 0.1%
22	3	< 0.1%
21	2	< 0.1%
20	1	< 0.1%
19	3	< 0.1%
18	7	< 0.1%
17	8	< 0.1%
16	11	< 0.1%

previous_contacts
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1729629989

Minimum	0
Maximum	7
Zeros	35563
Zeros (%)	86.3%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4949010798
Coefficient of variation (CV)	2.861311858
Kurtosis	20.10881622
Mean	0.1729629989
Median Absolute Deviation (MAD)	0
Skewness	3.832042243
Sum	7124
Variance	0.2449270788
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	35563	86.3%
1	4561	11.1%
2	754	1.8%
3	216	0.5%
4	70	0.2%
5	18	< 0.1%
6	5	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	35563	86.3%
1	4561	11.1%
2	754	1.8%
3	216	0.5%
4	70	0.2%
5	18	< 0.1%
6	5	< 0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
6	5	< 0.1%
5	18	< 0.1%
4	70	0.2%
3	216	0.5%
2	754	1.8%
1	4561	11.1%
0	35563	86.3%

previous_outcome
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.6 MiB

nonexistent	35563
failure	4252
success	1373

Length

Max length	11
Median length	11
Mean length	10.45372439
Min length	7

Characters and Unicode

Total characters	430568
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	nonexistent
2nd row	nonexistent
3rd row	nonexistent
4th row	nonexistent
5th row	nonexistent

Common Values

Value	Count	Frequency (%)
nonexistent	35563	86.3%
failure	4252	10.3%
success	1373	3.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
nonexistent	35563	86.3%
failure	4252	10.3%
success	1373	3.3%

Most occurring characters

Value	Count	Frequency (%)
n	106689	24.8%
e	76751	17.8%
t	71126	16.5%
i	39815	9.2%
s	39682	9.2%
o	35563	8.3%
x	35563	8.3%
u	5625	1.3%
f	4252	1.0%
a	4252	1.0%
Other values (3)	11250	2.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	430568	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	106689	24.8%
e	76751	17.8%
t	71126	16.5%
i	39815	9.2%
s	39682	9.2%
o	35563	8.3%
x	35563	8.3%
u	5625	1.3%
f	4252	1.0%
a	4252	1.0%
Other values (3)	11250	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	430568	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	106689	24.8%
e	76751	17.8%
t	71126	16.5%
i	39815	9.2%
s	39682	9.2%
o	35563	8.3%
x	35563	8.3%
u	5625	1.3%
f	4252	1.0%
a	4252	1.0%
Other values (3)	11250	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	430568	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	106689	24.8%
e	76751	17.8%
t	71126	16.5%
i	39815	9.2%
s	39682	9.2%
o	35563	8.3%
x	35563	8.3%
u	5625	1.3%
f	4252	1.0%
a	4252	1.0%
Other values (3)	11250	2.6%

emp_var_rate
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.08188550063

Minimum	-3.4
Maximum	1.4
Zeros	0
Zeros (%)	0.0%
Negative	17191
Negative (%)	41.7%
Memory size	321.9 KiB

Quantile statistics

Minimum	-3.4
5-th percentile	-2.9
Q1	-1.8
median	1.1
Q3	1.4
95-th percentile	1.4
Maximum	1.4
Range	4.8
Interquartile range (IQR)	3.2

Descriptive statistics

Standard deviation	1.570959741
Coefficient of variation (CV)	19.18483405
Kurtosis	-1.062631525
Mean	0.08188550063
Median Absolute Deviation (MAD)	0.3
Skewness	-0.7240955492
Sum	3372.7
Variance	2.467914506
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1.4	16234	39.4%
-1.8	9184	22.3%
1.1	7763	18.8%
-0.1	3683	8.9%
-2.9	1663	4.0%
-3.4	1071	2.6%
-1.7	773	1.9%
-1.1	635	1.5%
-3	172	0.4%
-0.2	10	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-3.4	1071	2.6%
-3	172	0.4%
-2.9	1663	4.0%
-1.8	9184	22.3%
-1.7	773	1.9%
-1.1	635	1.5%
-0.2	10	< 0.1%
-0.1	3683	8.9%
1.1	7763	18.8%
1.4	16234	39.4%

Value	Count	Frequency (%)
1.4	16234	39.4%
1.1	7763	18.8%
-0.1	3683	8.9%
-0.2	10	< 0.1%
-1.1	635	1.5%
-1.7	773	1.9%
-1.8	9184	22.3%
-2.9	1663	4.0%
-3	172	0.4%
-3.4	1071	2.6%

cons_price_idx
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	26
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	93.57566437

Minimum	92.201
Maximum	94.767
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	92.201
5-th percentile	92.713
Q1	93.075
median	93.749
Q3	93.994
95-th percentile	94.465
Maximum	94.767
Range	2.566
Interquartile range (IQR)	0.919

Descriptive statistics

Standard deviation	0.578840049
Coefficient of variation (CV)	0.00618579684
Kurtosis	-0.8298085772
Mean	93.57566437
Median Absolute Deviation (MAD)	0.38
Skewness	-0.2308876514
Sum	3854194.464
Variance	0.3350558023
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
93.994	7763	18.8%
93.918	6685	16.2%
92.893	5794	14.1%
93.444	5175	12.6%
94.465	4374	10.6%
93.2	3616	8.8%
93.075	2458	6.0%
92.201	770	1.9%
92.963	715	1.7%
92.431	447	1.1%
Other values (16)	3391	8.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
92.201	770	1.9%
92.379	267	0.6%
92.431	447	1.1%
92.469	178	0.4%
92.649	357	0.9%
92.713	172	0.4%
92.756	10	< 0.1%
92.843	282	0.7%
92.893	5794	14.1%
92.963	715	1.7%

Value	Count	Frequency (%)
94.767	128	0.3%
94.601	204	0.5%
94.465	4374	10.6%
94.215	311	0.8%
94.199	303	0.7%
94.055	229	0.6%
94.027	233	0.6%
93.994	7763	18.8%
93.918	6685	16.2%
93.876	212	0.5%

cons_conf_idx
Real number (ℝ)

HIGH CORRELATION

Distinct	26
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-40.50260027

Minimum	-50.8
Maximum	-26.9
Zeros	0
Zeros (%)	0.0%
Negative	41188
Negative (%)	100.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	-50.8
5-th percentile	-47.1
Q1	-42.7
median	-41.8
Q3	-36.4
95-th percentile	-33.6
Maximum	-26.9
Range	23.9
Interquartile range (IQR)	6.3

Descriptive statistics

Standard deviation	4.628197856
Coefficient of variation (CV)	-0.1142691537
Kurtosis	-0.3585583105
Mean	-40.50260027
Median Absolute Deviation (MAD)	4.4
Skewness	0.3031798587
Sum	-1668221.1
Variance	21.4202154
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
-36.4	7763	18.8%
-42.7	6685	16.2%
-46.2	5794	14.1%
-36.1	5175	12.6%
-41.8	4374	10.6%
-42	3616	8.8%
-47.1	2458	6.0%
-31.4	770	1.9%
-40.8	715	1.7%
-26.9	447	1.1%
Other values (16)	3391	8.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-50.8	128	0.3%
-50	282	0.7%
-49.5	204	0.5%
-47.1	2458	6.0%
-46.2	5794	14.1%
-45.9	10	< 0.1%
-42.7	6685	16.2%
-42	3616	8.8%
-41.8	4374	10.6%
-40.8	715	1.7%

Value	Count	Frequency (%)
-26.9	447	1.1%
-29.8	267	0.6%
-30.1	357	0.9%
-31.4	770	1.9%
-33	172	0.4%
-33.6	178	0.4%
-34.6	174	0.4%
-34.8	264	0.6%
-36.1	5175	12.6%
-36.4	7763	18.8%

euribor3m
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	316
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.621290813

Minimum	0.634
Maximum	5.045
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	0.634
5-th percentile	0.797
Q1	1.344
median	4.857
Q3	4.961
95-th percentile	4.966
Maximum	5.045
Range	4.411
Interquartile range (IQR)	3.617

Descriptive statistics

Standard deviation	1.734447405
Coefficient of variation (CV)	0.4789583313
Kurtosis	-1.406802622
Mean	3.621290813
Median Absolute Deviation (MAD)	0.108
Skewness	-0.7091879564
Sum	149153.726
Variance	3.0083078
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.857	2868	7.0%
4.962	2613	6.3%
4.963	2487	6.0%
4.961	1902	4.6%
4.856	1210	2.9%
4.964	1175	2.9%
1.405	1169	2.8%
4.965	1071	2.6%
4.864	1044	2.5%
4.96	1013	2.5%
Other values (306)	24636	59.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.634	8	< 0.1%
0.635	43	0.1%
0.636	14	< 0.1%
0.637	6	< 0.1%
0.638	7	< 0.1%
0.639	16	< 0.1%
0.64	10	< 0.1%
0.642	35	0.1%
0.643	23	0.1%
0.644	38	0.1%

Value	Count	Frequency (%)
5.045	9	< 0.1%
5	7	< 0.1%
4.97	172	0.4%
4.968	992	2.4%
4.967	643	1.6%
4.966	622	1.5%
4.965	1071	2.6%
4.964	1175	2.9%
4.963	2487	6.0%
4.962	2613	6.3%

no_of_employees
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5167.035911

Minimum	4963.6
Maximum	5228.1
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	321.9 KiB

Quantile statistics

Minimum	4963.6
5-th percentile	5017.5
Q1	5099.1
median	5191
Q3	5228.1
95-th percentile	5228.1
Maximum	5228.1
Range	264.5
Interquartile range (IQR)	129

Descriptive statistics

Standard deviation	72.25152767
Coefficient of variation (CV)	0.01398316732
Kurtosis	-0.003760375696
Mean	5167.035911
Median Absolute Deviation (MAD)	37.1
Skewness	-1.044262407
Sum	212819875.1
Variance	5220.28325
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
5228.1	16234	39.4%
5099.1	8534	20.7%
5191	7763	18.8%
5195.8	3683	8.9%
5076.2	1663	4.0%
5017.5	1071	2.6%
4991.6	773	1.9%
5008.7	650	1.6%
4963.6	635	1.5%
5023.5	172	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4963.6	635	1.5%
4991.6	773	1.9%
5008.7	650	1.6%
5017.5	1071	2.6%
5023.5	172	0.4%
5076.2	1663	4.0%
5099.1	8534	20.7%
5176.3	10	< 0.1%
5191	7763	18.8%
5195.8	3683	8.9%

Value	Count	Frequency (%)
5228.1	16234	39.4%
5195.8	3683	8.9%
5191	7763	18.8%
5176.3	10	< 0.1%
5099.1	8534	20.7%
5076.2	1663	4.0%
5023.5	172	0.4%
5017.5	1071	2.6%
5008.7	650	1.6%
4991.6	773	1.9%

y
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	40.3 KiB

False	36548
True	4640

Common Values
Chart

Value	Count	Frequency (%)
False	36548	88.7%
True	4640	11.3%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	age	job_type	marital_status	education_level	default_credit	housing_loan	personal_loan	contact_type	last_Cmonth	last_Cday	duration	no_of_contacts	previous_outcome	emp_var_rate	cons_price_idx	cons_conf_idx	euribor3m	no_of_employees	y
0	56	housemaid	married	basic.4y	no	no	no	telephone	may	mon	261	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
1	57	services	married	high.school	NaN	no	no	telephone	may	mon	149	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
2	37	services	married	high.school	no	yes	no	telephone	may	mon	226	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
3	40	admin.	married	basic.6y	no	no	no	telephone	may	mon	151	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
4	56	services	married	high.school	no	no	yes	telephone	may	mon	307	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
5	45	services	married	basic.9y	NaN	no	no	telephone	may	mon	198	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
6	59	admin.	married	professional.course	no	no	no	telephone	may	mon	139	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
7	41	blue-collar	married	NaN	NaN	no	no	telephone	may	mon	217	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
8	24	technician	single	professional.course	no	yes	no	telephone	may	mon	380	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no
9	25	services	single	high.school	no	yes	no	telephone	may	mon	50	1	nonexistent	1.1	93.994	-36.4	4.857	5191.0	no

Last rows

	age	job_type	marital_status	education_level	default_credit	housing_loan	personal_loan	contact_type	last_Cmonth	last_Cday	duration	no_of_contacts	passed_days	previous_contacts	previous_outcome	emp_var_rate	cons_price_idx	cons_conf_idx	euribor3m	no_of_employees	y
41178	62	retired	married	university.degree	no	no	no	cellular	nov	thu	483	2	6	3	success	-1.1	94.767	-50.8	1.031	4963.6	yes
41179	64	retired	divorced	professional.course	no	yes	no	cellular	nov	fri	151	3	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
41180	36	admin.	married	university.degree	no	no	no	cellular	nov	fri	254	2	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
41181	37	admin.	married	university.degree	no	yes	no	cellular	nov	fri	281	1	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	yes
41182	29	unemployed	single	basic.4y	no	yes	no	cellular	nov	fri	112	1	9	1	success	-1.1	94.767	-50.8	1.028	4963.6	no
41183	73	retired	married	professional.course	no	yes	no	cellular	nov	fri	334	1	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	yes
41184	46	blue-collar	married	professional.course	no	no	no	cellular	nov	fri	383	1	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
41185	56	retired	married	university.degree	no	yes	no	cellular	nov	fri	189	2	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	no
41186	44	technician	married	professional.course	no	no	no	cellular	nov	fri	442	1	0	0	nonexistent	-1.1	94.767	-50.8	1.028	4963.6	yes
41187	74	retired	married	professional.course	no	yes	no	cellular	nov	fri	239	3	0	1	failure	-1.1	94.767	-50.8	1.028	4963.6	no

Most frequently occurring

	age	job_type	marital_status	education_level	default_credit	housing_loan	personal_loan	contact_type	last_Cmonth	last_Cday	duration	no_of_contacts	previous_outcome	emp_var_rate	cons_price_idx	cons_conf_idx	euribor3m	no_of_employees	y	# duplicates
0	24	services	single	high.school	no	yes	no	cellular	apr	tue	114	1	nonexistent	-1.8	93.075	-47.1	1.423	5099.1	no	2
1	27	technician	single	professional.course	no	no	no	cellular	jul	mon	331	2	nonexistent	1.4	93.918	-42.7	4.962	5228.1	no	2
2	32	technician	single	professional.course	no	yes	no	cellular	jul	thu	128	1	nonexistent	1.4	93.918	-42.7	4.968	5228.1	no	2
3	35	admin.	married	university.degree	no	yes	no	cellular	may	fri	348	4	nonexistent	-1.8	92.893	-46.2	1.313	5099.1	no	2
4	39	admin.	married	university.degree	no	no	no	cellular	nov	tue	123	2	nonexistent	-0.1	93.200	-42.0	4.153	5195.8	no	2
5	39	blue-collar	married	basic.6y	no	no	no	telephone	may	thu	124	1	nonexistent	1.1	93.994	-36.4	4.855	5191.0	no	2
6	41	technician	married	professional.course	no	yes	no	cellular	aug	tue	127	1	nonexistent	1.4	93.444	-36.1	4.966	5228.1	no	2
7	45	admin.	married	university.degree	no	no	no	cellular	jul	thu	252	1	nonexistent	-2.9	92.469	-33.6	1.072	5076.2	yes	2
8	47	technician	divorced	high.school	no	yes	no	cellular	jul	thu	43	3	nonexistent	1.4	93.918	-42.7	4.962	5228.1	no	2
9	71	retired	single	university.degree	no	no	no	telephone	oct	tue	120	1	nonexistent	-3.4	92.431	-26.9	0.742	5017.5	no	2

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Other Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Most occurring scripts